Copyright: ©Author(s) 2026.
World J Gastrointest Oncol. Oct 15, 2026; 18(10): 122464
Published online Oct 15, 2026. doi: 10.4251/wjgo.122464
Published online Oct 15, 2026. doi: 10.4251/wjgo.122464
Figure 5 Receiver operating characteristic curves of each model.
A: Comparison of the combined model, clinical imaging model, and 10-mm peritumoral model in the training set; B: Comparison of the combined model, clinical imaging model, and 10-mm peritumoral model in the internal validation set; C: Comparison of the combined model, clinical imaging model, and 10-mm peritumoral model in the external validation set. AUC: Area under the curve.
- Citation: Li YH, Yao L, Qian GX, Lei XD, Tang ZQ, Guo BY, Du R, Zhu Y, Jia WD. Deep learning-enhanced peritumoral radiomics predicts early recurrence after hepatocellular carcinoma ablation: A two-center study. World J Gastrointest Oncol 2026; 18(10): 122464
- URL: https://www.wjgnet.com/1948-5204/full/v18/i10/122464.htm
- DOI: https://dx.doi.org/10.4251/wjgo.122464